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Large-alphabet sequence modelling - a comparative study

Shao, Wen


Most raw data is not binary, but over some often large and structured alphabet. Sometimes it is convenient to deal with binarised data sequence, but typically exploiting the original structure of the data significantly improves performance in many practical applications. In this thesis, we study Martin-Lof random sequences that are maximally incompressible and provide a topological view on the size of the set of random sequences. We also investigate the relationship between binary data...[Show more]

CollectionsOpen Access Theses
Date published: 2014
Type: Thesis (MPhil)
DOI: 10.25911/5d51415ba1671


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